Electric Drive Units (EDUs) are at the heart of modern electric vehicles, combining the electric motor and transmission into a single, compact system. These units are crucial for achieving the efficiency, performance, and reliability expected in electric cars.
A key challenge in the design of EDUs is ensuring effective lubrication. Proper lubrication minimizes friction, reduces wear on components, and helps dissipate heat, all of which are critical for maintaining the longevity and efficiency of the system. Additionally, as EDUs operate at high speeds and under varying loads, optimizing lubrication becomes essential for achieving peak performance while meeting stringent durability requirements.
This simulation case explores the behavior of lubrication within an EDU, focusing on how oil is distributed and interacts with critical components under realistic operating conditions.
Objective of Part II: Examine Critical Regions of the E-Engine Towards Lubrication
The focus of Parts II and III is to analyze lubrication in the two main regions of the Electric Drive Unit (EDU): the E-engine and the transmission. Although addressed in a single comprehensive simulation, splitting the study into these parts allows for clearer insights and reduced complexity.
Part II specifically addresses the E-engine, which includes critical components such as the rotor, windings (WDG), and stator. Unlike the transmission, where lubrication primarily minimizes friction and wear, the primary function of the lubricant in the E-engine is heat dissipation. To evaluate this, the simulation focuses on monitoring oil coverage rates at critical regions and analyzing flow behavior through strategically placed sample windows. These measurements provide valuable insights into the lubricant’s ability to dissipate heat effectively in this region.
Case Description
The general setup of the EDU simulation is depicted in the image below. To avoid duplication, this part exclusively describes the E-engine section. For a detailed explanation of the transmission setup, please refer to Part III. .
The simulation incorporates eight inlets, each corresponding to a channel within the rotor. The flow rates for these inlets are derived from the results in Part I. :
- Sample 1: 1.15 L/min
- Sample 2: 1.80 L/min
- Sample 3: 1.25 L/min
- Sample 4: 1.80 L/min
The inlets are connected to a single outlet (highlighted as the red box in the image). This setup ensures that the fluid exits the computational domain through the outlet at a flow rate of 12 L/min. The fluid is then recycled and redistributed to the inlets to maintain the predefined flow rates.
Like in Part I the final rotation speed of the rotor is 2000 RPM. The only different is that it ramps up within 0.2 seconds.
The sample windows used to monitor the simulation are shown in the image below:
A particle size of 0.064 mm was used and a total particle number of around 5 million particles. Initial particle distribution is shown in the image below:
仿真结果
Bearings
The performance of the two rotor bearings are analyzed below, with diagrams illustrating the lubrication behavior over time.
Bearing 2 (Diagram on the left):
- Steady state is achieved after approximately 1 second.
- Around 2.25 ml of lubricant is consistently present within the bearing for lubrication.
- The flow rate into and out of the bearing stabilizes at approximately 2.5 L/min.
Bearing 1 (Diagram on the right):
- Steady state is achieved after approximately 3 seconds.
- Around 8 ml of lubricant is consistently present within the bearing for lubrication.
- The flow rate into and out of the bearing stabilizes at approximately 5 L/min.
The rendered images below illustrate the state of Bearing 2 (left) and Bearing 1 (right) after 5 seconds of simulation:
Winding
- The diagram below represents the flow rate in and out of the winding sample.
- After 5 seconds, the inflow and outflow are nearly equalized.
- At this point, the inflow is approximately 27.5 L/min, while the outflow is 26.5 L/min, indicating a slight ongoing accumulation of fluid in this region. This suggests that the simulation has not yet fully reached a steady state in this area.
- The lubricant volume in the sample is approximately 250 ml, meaning that statistically, the fluid is exchanged twice per second.
Rendered Images of Winding Fluid Distribution
The rendered images below provide insights into the fluid distribution and coverage rate in the winding region after 5 seconds of simulation:
- Left Image: The fluid distribution in the winding region is shown with the solid winding hidden for better visualization.
- Right Image: The solid winding is displayed, with the fluid hidden, and the time-averaged coverage rate (averaging time: 1 second) is overlaid on the winding surface.
Key Observations:
- The fluid is primarily located in the gaps between the ribs of the winding.
- The highest coverage rates are observed at the ends of the windings, where fluid is directly sprayed from the rotor.
总结
This case study focuses on analyzing lubrication behavior within the E-engine section of an Electric Drive Unit (EDU), a critical component of modern electric vehicles. The study aims to simulate the lubrication for effective heat dissipation and ensure the durability and efficiency of the system.
Key findings include:
- Bearings: Both rotor bearings achieve steady-state lubrication, with Bearing 2 stabilizing at 2.5 L/min inflow and Bearing 1 at 5 L/min. Lubricant volumes of 2.25 ml and 8 ml, respectively, ensure consistent performance under operating conditions.
- Winding: The fluid distribution highlights gaps between the winding ribs as primary accumulation points, with the highest coverage at the winding ends where direct spray from the rotor occurs. Lubricant exchange is twice per second, ensuring efficient cooling and heat dissipation.
By leveraging high-resolution simulations and strategically placed sample windows, the study provides valuable insights into the behavior of lubrication in critical E-engine regions. This knowledge supports the design of more efficient and reliable EDUs, contributing to improved performance and durability in electric vehicles.
